As graphics processing units (GPUs) become increasingly ubiquitous in the arena of hardware-accelerated applications (be it graphics applications or otherwise), they may be expected to provide a rich set of features to facilitate the efficient and correct implementation of a wide range of algorithms. One such feature is conservative rasterization.
In a standard rasterization pipeline, an inclusion test is carried out at a sample point usually being at the center of the pixel. If the sample is calculated to be inside the triangle, a fragment is generated for that pixel. The pixel is rejected otherwise. While this process succeeds in including all the pixels that are wholly contained within the triangle, several pixels along the edges may not be included even though they overlap the triangle. This is because the center of such pixels along the edges is outside the edge of the triangle.
Conservative rasterization is a rasterization technique that attempts to guarantee the inclusion of all the pixels that overlap, even partially, with each primitive. However, due to limited precision in hardware, conventional conservative rasterization may not always include all pixels that overlap a primitive.